Overview

Brought to you by YData

Dataset statistics

Number of variables13
Number of observations505354
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.1 MiB
Average record size in memory104.0 B

Variable types

Numeric12
Categorical1

Alerts

Avg_Hillshade is highly overall correlated with Hillshade_Noon and 1 other fieldsHigh correlation
Elevation is highly overall correlated with Soil_Type and 1 other fieldsHigh correlation
Elevation_x_Slope is highly overall correlated with SlopeHigh correlation
Hillshade_Noon is highly overall correlated with Avg_HillshadeHigh correlation
Horizontal_Distance_To_Fire_Points is highly overall correlated with Hydro_Road_Fire_DistanceHigh correlation
Horizontal_Distance_To_Roadways is highly overall correlated with Hydro_Road_Fire_DistanceHigh correlation
Hydro_Road_Fire_Distance is highly overall correlated with Horizontal_Distance_To_Fire_Points and 1 other fieldsHigh correlation
Slope is highly overall correlated with Avg_Hillshade and 1 other fieldsHigh correlation
Soil_Type is highly overall correlated with ElevationHigh correlation
Wilderness_Area is highly overall correlated with ElevationHigh correlation
Horizontal_Distance_To_Hydrology has 21630 (4.3%) zeros Zeros

Reproduction

Analysis started2025-06-09 19:38:05.892900
Analysis finished2025-06-09 19:38:30.528956
Duration24.64 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Hillshade_Noon
Real number (ℝ)

High correlation 

Distinct185
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.87896182
Minimum0
Maximum1
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:30.632782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.73622047
Q10.83858268
median0.88976378
Q30.93307087
95-th percentile0.98425197
Maximum1
Range1
Interquartile range (IQR)0.094488189

Descriptive statistics

Standard deviation0.077089647
Coefficient of variation (CV)0.087705341
Kurtosis2.4443385
Mean0.87896182
Median Absolute Deviation (MAD)0.047244094
Skewness-1.1404263
Sum444186.87
Variance0.0059428137
MonotonicityNot monotonic
2025-06-09T22:38:30.745949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9094488189 12314
 
2.4%
0.8976377953 12230
 
2.4%
0.9173228346 12063
 
2.4%
0.905511811 11975
 
2.4%
0.9015748031 11849
 
2.3%
0.9212598425 11805
 
2.3%
0.8937007874 11601
 
2.3%
0.8897637795 11594
 
2.3%
0.8779527559 11564
 
2.3%
0.8858267717 11495
 
2.3%
Other values (175) 386864
76.6%
ValueCountFrequency (%)
0 5
< 0.1%
0.1181102362 1
 
< 0.1%
0.157480315 1
 
< 0.1%
0.1653543307 1
 
< 0.1%
0.1771653543 1
 
< 0.1%
0.2086614173 2
 
< 0.1%
0.2480314961 1
 
< 0.1%
0.2519685039 1
 
< 0.1%
0.2677165354 1
 
< 0.1%
0.2795275591 1
 
< 0.1%
ValueCountFrequency (%)
1 3981
0.8%
0.9960629921 4664
0.9%
0.9921259843 5492
1.1%
0.9881889764 5864
1.2%
0.9842519685 6488
1.3%
0.9803149606 6356
1.3%
0.9763779528 6907
1.4%
0.9724409449 7617
1.5%
0.968503937 7453
1.5%
0.9645669291 7352
1.5%

Hydro_Road_Fire_Distance
Real number (ℝ)

High correlation 

Distinct12679
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.35297117
Minimum0
Maximum1
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:30.828204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.10281593
Q10.2065526
median0.31934321
Q30.46919359
95-th percentile0.72792143
Maximum1
Range1
Interquartile range (IQR)0.26264099

Descriptive statistics

Standard deviation0.19013593
Coefficient of variation (CV)0.53867268
Kurtosis-0.029145393
Mean0.35297117
Median Absolute Deviation (MAD)0.12460677
Skewness0.7353494
Sum178375.39
Variance0.03615167
MonotonicityNot monotonic
2025-06-09T22:38:30.912209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.218061843 134
 
< 0.1%
0.2219749866 125
 
< 0.1%
0.2185222128 123
 
< 0.1%
0.215299624 122
 
< 0.1%
0.4014424921 121
 
< 0.1%
0.2309521983 118
 
< 0.1%
0.2234328244 117
 
< 0.1%
0.2638686411 116
 
< 0.1%
0.2367835495 116
 
< 0.1%
0.1566024707 116
 
< 0.1%
Other values (12669) 504146
99.8%
ValueCountFrequency (%)
0 1
< 0.1%
0.0005370981355 1
< 0.1%
0.001304381186 1
< 0.1%
0.003222588813 2
< 0.1%
0.003376045423 1
< 0.1%
0.003759686949 1
< 0.1%
0.004143328474 1
< 0.1%
0.004296785084 1
< 0.1%
0.004450241694 2
< 0.1%
0.005524437965 1
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.9994629019 1
< 0.1%
0.9989258037 1
< 0.1%
0.9986956188 1
< 0.1%
0.9984654339 1
< 0.1%
0.9979283358 1
< 0.1%
0.9978516075 1
< 0.1%
0.9976981508 1
< 0.1%
0.9976214225 2
< 0.1%
0.9975446942 2
< 0.1%

Horizontal_Distance_To_Roadways
Real number (ℝ)

High correlation 

Distinct5785
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.34171421
Minimum0
Maximum1
Zeros96
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:30.991719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.054938879
Q10.16017985
median0.29197696
Q30.48826753
95-th percentile0.78277364
Maximum1
Range1
Interquartile range (IQR)0.32808768

Descriptive statistics

Standard deviation0.22487219
Coefficient of variation (CV)0.65807093
Kurtosis-0.53780115
Mean0.34171421
Median Absolute Deviation (MAD)0.15245188
Skewness0.65607631
Sum172686.64
Variance0.050567502
MonotonicityNot monotonic
2025-06-09T22:38:31.072159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02107629619 1078
 
0.2%
0.08683434031 882
 
0.2%
0.1264577772 821
 
0.2%
0.1433188141 805
 
0.2%
0.1391035549 777
 
0.2%
0.1348882956 764
 
0.2%
0.0547983701 763
 
0.2%
0.1601798511 736
 
0.1%
0.1475340733 726
 
0.1%
0.105381481 725
 
0.1%
Other values (5775) 497277
98.4%
ValueCountFrequency (%)
0 96
 
< 0.1%
0.004215259238 267
0.1%
0.005901362934 153
 
< 0.1%
0.008430518477 280
0.1%
0.009414078966 249
< 0.1%
0.01194323451 293
0.1%
0.01264577772 331
0.1%
0.01334832092 317
0.1%
0.01517493326 537
0.1%
0.01686103695 559
0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.9998594914 1
< 0.1%
0.9992974568 1
< 0.1%
0.9971898272 1
< 0.1%
0.996487284 1
< 0.1%
0.9957847408 2
< 0.1%
0.9950821976 1
< 0.1%
0.9946606716 1
< 0.1%
0.994520163 2
< 0.1%
0.9932555852 1
< 0.1%

Hillshade_9am
Real number (ℝ)

Distinct207
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83575869
Minimum0
Maximum1
Zeros13
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:31.152962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.62992126
Q10.78346457
median0.85826772
Q30.90944882
95-th percentile0.96456693
Maximum1
Range1
Interquartile range (IQR)0.12598425

Descriptive statistics

Standard deviation0.10484011
Coefficient of variation (CV)0.12544303
Kurtosis2.1182007
Mean0.83575869
Median Absolute Deviation (MAD)0.059055118
Skewness-1.2439666
Sum422354
Variance0.010991448
MonotonicityNot monotonic
2025-06-09T22:38:31.241482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8897637795 10413
 
2.1%
0.8976377953 10242
 
2.0%
0.8818897638 10051
 
2.0%
0.905511811 10049
 
2.0%
0.8779527559 9782
 
1.9%
0.874015748 9720
 
1.9%
0.9173228346 9416
 
1.9%
0.8937007874 9382
 
1.9%
0.8858267717 9243
 
1.8%
0.8700787402 9239
 
1.8%
Other values (197) 407817
80.7%
ValueCountFrequency (%)
0 13
< 0.1%
0.1417322835 1
 
< 0.1%
0.1811023622 2
 
< 0.1%
0.1968503937 1
 
< 0.1%
0.2047244094 1
 
< 0.1%
0.2086614173 1
 
< 0.1%
0.2125984252 3
 
< 0.1%
0.2165354331 1
 
< 0.1%
0.2204724409 5
 
< 0.1%
0.2244094488 2
 
< 0.1%
ValueCountFrequency (%)
1 1641
 
0.3%
0.9960629921 1822
 
0.4%
0.9921259843 2123
0.4%
0.9881889764 2409
0.5%
0.9842519685 2766
0.5%
0.9803149606 3116
0.6%
0.9763779528 3249
0.6%
0.9724409449 3691
0.7%
0.968503937 4069
0.8%
0.9645669291 4560
0.9%

Avg_Hillshade
Real number (ℝ)

High correlation 

Distinct384
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.88483176
Minimum0
Maximum1
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:31.321994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.73443223
Q10.84615385
median0.8992674
Q30.93956044
95-th percentile0.98534799
Maximum1
Range1
Interquartile range (IQR)0.093406593

Descriptive statistics

Standard deviation0.07908722
Coefficient of variation (CV)0.089381081
Kurtosis3.0701699
Mean0.88483176
Median Absolute Deviation (MAD)0.045787546
Skewness-1.3616708
Sum447153.27
Variance0.0062547883
MonotonicityNot monotonic
2025-06-09T22:38:31.403155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9212454212 6583
 
1.3%
0.9139194139 6186
 
1.2%
0.9175824176 6168
 
1.2%
0.9322344322 5970
 
1.2%
0.9047619048 5963
 
1.2%
0.9249084249 5952
 
1.2%
0.9010989011 5878
 
1.2%
0.8992673993 5798
 
1.1%
0.9065934066 5781
 
1.1%
0.9285714286 5696
 
1.1%
Other values (374) 445379
88.1%
ValueCountFrequency (%)
0 1
< 0.1%
0.01465201465 1
< 0.1%
0.13003663 1
< 0.1%
0.1538461538 1
< 0.1%
0.1648351648 2
< 0.1%
0.1758241758 1
< 0.1%
0.1794871795 1
< 0.1%
0.2106227106 1
< 0.1%
0.2289377289 1
< 0.1%
0.2435897436 1
< 0.1%
ValueCountFrequency (%)
1 247
 
< 0.1%
0.9981684982 1927
0.4%
0.9963369963 2939
0.6%
0.9945054945 3181
0.6%
0.9926739927 3415
0.7%
0.9908424908 3115
0.6%
0.989010989 3447
0.7%
0.9871794872 3739
0.7%
0.9853479853 3372
0.7%
0.9835164835 4121
0.8%

Elevation
Real number (ℝ)

High correlation 

Distinct1978
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.54656732
Minimum0
Maximum1
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:31.485757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.26113057
Q10.47773887
median0.56428214
Q30.64182091
95-th percentile0.73186593
Maximum1
Range1
Interquartile range (IQR)0.16408204

Descriptive statistics

Standard deviation0.13781103
Coefficient of variation (CV)0.25213916
Kurtosis1.0931128
Mean0.54656732
Median Absolute Deviation (MAD)0.08154077
Skewness-0.89179409
Sum276209.98
Variance0.018991879
MonotonicityNot monotonic
2025-06-09T22:38:31.574203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5547773887 1625
 
0.3%
0.5517758879 1613
 
0.3%
0.5662831416 1613
 
0.3%
0.5567783892 1609
 
0.3%
0.5597798899 1603
 
0.3%
0.5582791396 1599
 
0.3%
0.5647823912 1554
 
0.3%
0.5482741371 1524
 
0.3%
0.5532766383 1519
 
0.3%
0.5467733867 1514
 
0.3%
Other values (1968) 489581
96.9%
ValueCountFrequency (%)
0 1
 
< 0.1%
0.0005002501251 1
 
< 0.1%
0.00100050025 1
 
< 0.1%
0.0020010005 1
 
< 0.1%
0.003501750875 1
 
< 0.1%
0.004002001001 1
 
< 0.1%
0.004502251126 1
 
< 0.1%
0.006003001501 3
< 0.1%
0.006503251626 4
< 0.1%
0.007003501751 1
 
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
0.9994997499 1
 
< 0.1%
0.9989994997 1
 
< 0.1%
0.9974987494 1
 
< 0.1%
0.9969984992 1
 
< 0.1%
0.9964982491 2
 
< 0.1%
0.995997999 1
 
< 0.1%
0.9954977489 4
< 0.1%
0.9949974987 1
 
< 0.1%
0.9939969985 6
< 0.1%

Horizontal_Distance_To_Hydrology
Real number (ℝ)

Zeros 

Distinct551
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.19052047
Minimum0
Maximum1
Zeros21630
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:31.663512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.021474588
Q10.077308518
median0.15461704
Q30.27129563
95-th percentile0.48246242
Maximum1
Range1
Interquartile range (IQR)0.19398712

Descriptive statistics

Standard deviation0.15110145
Coefficient of variation (CV)0.79309826
Kurtosis1.6070835
Mean0.19052047
Median Absolute Deviation (MAD)0.093772369
Skewness1.188776
Sum96280.281
Variance0.022831649
MonotonicityNot monotonic
2025-06-09T22:38:31.752023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0214745884 29993
 
5.9%
0 21630
 
4.3%
0.107372942 18274
 
3.6%
0.04294917681 16778
 
3.3%
0.0479599141 13454
 
2.7%
0.03006442377 12960
 
2.6%
0.07730851825 12702
 
2.5%
0.06084466714 12156
 
2.4%
0.06442376521 9757
 
1.9%
0.08589835361 9343
 
1.8%
Other values (541) 348307
68.9%
ValueCountFrequency (%)
0 21630
4.3%
0.0214745884 29993
5.9%
0.03006442377 12960
2.6%
0.04294917681 16778
3.3%
0.0479599141 13454
2.7%
0.06084466714 12156
2.4%
0.06442376521 9757
 
1.9%
0.06800286328 8120
 
1.6%
0.07730851825 12702
2.5%
0.08589835361 9343
 
1.8%
ValueCountFrequency (%)
1 1
< 0.1%
0.9949892627 2
< 0.1%
0.9899785254 2
< 0.1%
0.9892627058 1
< 0.1%
0.9849677881 1
< 0.1%
0.9813886901 1
< 0.1%
0.9806728704 1
< 0.1%
0.9799570508 1
< 0.1%
0.9792412312 2
< 0.1%
0.9742304939 2
< 0.1%

Horizontal_Distance_To_Fire_Points
Real number (ℝ)

High correlation 

Distinct5827
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.28023646
Minimum0
Maximum1
Zeros45
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:31.835537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.056879967
Q10.14275756
median0.24048515
Q30.36135508
95-th percentile0.70946605
Maximum1
Range1
Interquartile range (IQR)0.21859752

Descriptive statistics

Standard deviation0.18929568
Coefficient of variation (CV)0.67548557
Kurtosis1.5080032
Mean0.28023646
Median Absolute Deviation (MAD)0.10748641
Skewness1.266097
Sum141618.62
Variance0.035832855
MonotonicityNot monotonic
2025-06-09T22:38:31.921817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.08615641991 1244
 
0.2%
0.07542172034 981
 
0.2%
0.0846228914 930
 
0.2%
0.1313258051 856
 
0.2%
0.1389934477 844
 
0.2%
0.09758817789 833
 
0.2%
0.1012128816 798
 
0.2%
0.1048375854 782
 
0.2%
0.1254705144 774
 
0.2%
0.1338352154 768
 
0.2%
Other values (5817) 496544
98.3%
ValueCountFrequency (%)
0 45
 
< 0.1%
0.004182350481 184
< 0.1%
0.005855290673 183
< 0.1%
0.008364700962 182
< 0.1%
0.009340582741 370
0.1%
0.01184999303 183
< 0.1%
0.01254705144 182
< 0.1%
0.01324410986 366
0.1%
0.01505646173 369
0.1%
0.01672940192 180
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.9998605883 1
< 0.1%
0.9993029416 1
< 0.1%
0.9967935313 1
< 0.1%
0.9960964729 1
< 0.1%
0.9956782378 1
< 0.1%
0.9955388262 2
< 0.1%
0.9953994145 1
< 0.1%
0.9941447093 1
< 0.1%
0.9934476509 1
< 0.1%

Slope
Real number (ℝ)

High correlation 

Distinct67
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.20859689
Minimum0
Maximum1
Zeros621
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:32.004330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.060606061
Q10.12121212
median0.1969697
Q30.27272727
95-th percentile0.42424242
Maximum1
Range1
Interquartile range (IQR)0.15151515

Descriptive statistics

Standard deviation0.11323937
Coefficient of variation (CV)0.5428622
Kurtosis0.75038989
Mean0.20859689
Median Absolute Deviation (MAD)0.075757576
Skewness0.85685891
Sum105415.27
Variance0.012823154
MonotonicityNot monotonic
2025-06-09T22:38:32.089562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1515151515 30511
 
6.0%
0.1666666667 30123
 
6.0%
0.1818181818 29324
 
5.8%
0.1363636364 29017
 
5.7%
0.196969697 28187
 
5.6%
0.1212121212 27610
 
5.5%
0.2121212121 25932
 
5.1%
0.2272727273 24691
 
4.9%
0.1060606061 24304
 
4.8%
0.09090909091 22768
 
4.5%
Other values (57) 232887
46.1%
ValueCountFrequency (%)
0 621
 
0.1%
0.01515151515 3485
 
0.7%
0.0303030303 7301
 
1.4%
0.04545454545 10951
 
2.2%
0.06060606061 15310
3.0%
0.07575757576 19417
3.8%
0.09090909091 22768
4.5%
0.1060606061 24304
4.8%
0.1212121212 27610
5.5%
0.1363636364 29017
5.7%
ValueCountFrequency (%)
1 1
 
< 0.1%
0.9848484848 2
 
< 0.1%
0.9696969697 1
 
< 0.1%
0.9545454545 1
 
< 0.1%
0.9393939394 2
 
< 0.1%
0.9242424242 4
< 0.1%
0.9090909091 2
 
< 0.1%
0.8939393939 3
< 0.1%
0.8787878788 1
 
< 0.1%
0.8636363636 7
< 0.1%

Elevation_x_Slope
Real number (ℝ)

High correlation 

Distinct37825
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.19572668
Minimum0
Maximum1
Zeros621
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:32.174295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.054874073
Q10.12053885
median0.18209684
Q30.25631101
95-th percentile0.3833073
Maximum1
Range1
Interquartile range (IQR)0.13577216

Descriptive statistics

Standard deviation0.10242268
Coefficient of variation (CV)0.52329443
Kurtosis0.91042054
Mean0.19572668
Median Absolute Deviation (MAD)0.066663413
Skewness0.80115176
Sum98911.263
Variance0.010490406
MonotonicityNot monotonic
2025-06-09T22:38:32.258807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 621
 
0.1%
0.1873096447 163
 
< 0.1%
0.1733112066 159
 
< 0.1%
0.1918781726 157
 
< 0.1%
0.1440843421 154
 
< 0.1%
0.1453533776 146
 
< 0.1%
0.1895939086 146
 
< 0.1%
0.1305544709 143
 
< 0.1%
0.1444260055 143
 
< 0.1%
0.2389691527 142
 
< 0.1%
Other values (37815) 503380
99.6%
ValueCountFrequency (%)
0 621
0.1%
0.009415267474 1
 
< 0.1%
0.009468957439 1
 
< 0.1%
0.009820382663 1
 
< 0.1%
0.01019133151 2
 
< 0.1%
0.01024990238 1
 
< 0.1%
0.0102645451 1
 
< 0.1%
0.01035240141 1
 
< 0.1%
0.01035728231 1
 
< 0.1%
0.01039144865 1
 
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.9947676689 1
< 0.1%
0.9815989848 1
< 0.1%
0.9556618508 1
< 0.1%
0.9448408825 1
< 0.1%
0.9239408434 1
< 0.1%
0.9062524405 1
< 0.1%
0.9025380711 1
< 0.1%
0.875204998 1
< 0.1%
0.8654822335 1
< 0.1%

Wilderness_Area
Real number (ℝ)

High correlation 

Distinct40
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.67163
Minimum0
Maximum39
Zeros3031
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:32.332317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q120
median28
Q330
95-th percentile37
Maximum39
Range39
Interquartile range (IQR)10

Descriptive statistics

Standard deviation9.1508803
Coefficient of variation (CV)0.38657584
Kurtosis-0.28933434
Mean23.67163
Median Absolute Deviation (MAD)4
Skewness-0.76966211
Sum11962553
Variance83.738611
MonotonicityNot monotonic
2025-06-09T22:38:32.408541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
28 115174
22.8%
22 48686
9.6%
31 46440
9.2%
32 33897
 
6.7%
29 30170
 
6.0%
11 29971
 
5.9%
9 26929
 
5.3%
21 25682
 
5.1%
30 24253
 
4.8%
23 16959
 
3.4%
Other values (30) 107193
21.2%
ValueCountFrequency (%)
0 3031
 
0.6%
1 4918
 
1.0%
2 2531
 
0.5%
3 7619
 
1.5%
4 1597
 
0.3%
5 6575
 
1.3%
6 105
 
< 0.1%
7 179
 
< 0.1%
8 1147
 
0.2%
9 26929
5.3%
ValueCountFrequency (%)
39 6834
 
1.4%
38 10406
 
2.1%
37 13519
 
2.7%
36 298
 
0.1%
35 119
 
< 0.1%
34 1391
 
0.3%
33 706
 
0.1%
32 33897
6.7%
31 46440
9.2%
30 24253
4.8%

Soil_Type
Categorical

High correlation 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.9 MiB
0.0
260796 
2.0
199161 
3.0
36968 
1.0
 
8429

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1516062
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 260796
51.6%
2.0 199161
39.4%
3.0 36968
 
7.3%
1.0 8429
 
1.7%

Length

2025-06-09T22:38:32.480140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-09T22:38:32.554650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0.0 260796
51.6%
2.0 199161
39.4%
3.0 36968
 
7.3%
1.0 8429
 
1.7%

Most occurring characters

ValueCountFrequency (%)
0 766150
50.5%
. 505354
33.3%
2 199161
 
13.1%
3 36968
 
2.4%
1 8429
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1516062
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 766150
50.5%
. 505354
33.3%
2 199161
 
13.1%
3 36968
 
2.4%
1 8429
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1516062
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 766150
50.5%
. 505354
33.3%
2 199161
 
13.1%
3 36968
 
2.4%
1 8429
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1516062
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 766150
50.5%
. 505354
33.3%
2 199161
 
13.1%
3 36968
 
2.4%
1 8429
 
0.6%

Cover_Type
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0589349
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 MiB
2025-06-09T22:38:32.601165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3893957
Coefficient of variation (CV)0.67481283
Kurtosis4.9724135
Mean2.0589349
Median Absolute Deviation (MAD)0
Skewness2.2809236
Sum1040491
Variance1.9304204
MonotonicityNot monotonic
2025-06-09T22:38:32.650168image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 254165
50.3%
1 178709
35.4%
3 28058
 
5.6%
7 17532
 
3.5%
6 14851
 
2.9%
5 9292
 
1.8%
4 2747
 
0.5%
ValueCountFrequency (%)
1 178709
35.4%
2 254165
50.3%
3 28058
 
5.6%
4 2747
 
0.5%
5 9292
 
1.8%
6 14851
 
2.9%
7 17532
 
3.5%
ValueCountFrequency (%)
7 17532
 
3.5%
6 14851
 
2.9%
5 9292
 
1.8%
4 2747
 
0.5%
3 28058
 
5.6%
2 254165
50.3%
1 178709
35.4%

Interactions

2025-06-09T22:38:28.123056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:11.924022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-09T22:38:14.379982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-09T22:38:16.663603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:17.797727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:18.955966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:20.283005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:24.135836image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-09T22:38:12.263947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-09T22:38:28.568524image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-09T22:38:14.093473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:15.231564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:16.372322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:17.510845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:18.635051image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:19.943388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:23.792638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:25.100564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:26.396140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:27.768571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:29.270492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:12.967517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:14.186684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:15.323718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:16.468576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:17.604365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:18.750985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:20.058263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:23.906933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:25.203076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:26.506260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:27.889227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:29.383784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:13.095538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:14.284848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:15.424570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:16.567098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:17.704229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:18.857502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:20.173295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:24.022173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:25.316140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:26.621492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-09T22:38:28.006741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-06-09T22:38:32.703416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Avg_HillshadeCover_TypeElevationElevation_x_SlopeHillshade_9amHillshade_NoonHorizontal_Distance_To_Fire_PointsHorizontal_Distance_To_HydrologyHorizontal_Distance_To_RoadwaysHydro_Road_Fire_DistanceSlopeSoil_TypeWilderness_Area
Avg_Hillshade1.000-0.0780.193-0.499-0.1940.9860.0180.0360.2190.158-0.5230.1380.022
Cover_Type-0.0781.000-0.4930.084-0.009-0.063-0.121-0.007-0.226-0.2230.1670.482-0.224
Elevation0.193-0.4931.000-0.0230.0260.1860.1290.2610.4170.368-0.1750.5430.536
Elevation_x_Slope-0.4990.084-0.0231.000-0.119-0.443-0.1320.057-0.155-0.1780.9840.1320.128
Hillshade_9am-0.194-0.0090.026-0.1191.000-0.0860.126-0.0390.0070.067-0.1250.1960.009
Hillshade_Noon0.986-0.0630.186-0.443-0.0861.0000.0200.0320.2090.152-0.4680.1430.020
Horizontal_Distance_To_Fire_Points0.018-0.1210.129-0.1320.1260.0201.0000.0740.3710.735-0.1690.2900.072
Horizontal_Distance_To_Hydrology0.036-0.0070.2610.057-0.0390.0320.0741.0000.0720.1540.0130.1060.196
Horizontal_Distance_To_Roadways0.219-0.2260.417-0.1550.0070.2090.3710.0721.0000.880-0.2280.3630.191
Hydro_Road_Fire_Distance0.158-0.2230.368-0.1780.0670.1520.7350.1540.8801.000-0.2470.4240.175
Slope-0.5230.167-0.1750.984-0.125-0.468-0.1690.013-0.228-0.2471.0000.2060.030
Soil_Type0.1380.4820.5430.1320.1960.1430.2900.1060.3630.4240.2061.0000.459
Wilderness_Area0.022-0.2240.5360.1280.0090.0200.0720.1960.1910.1750.0300.4591.000

Missing values

2025-06-09T22:38:29.482912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-09T22:38:29.844737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Hillshade_NoonHydro_Road_Fire_DistanceHorizontal_Distance_To_RoadwaysHillshade_9amAvg_HillshadeElevationHorizontal_Distance_To_HydrologyHorizontal_Distance_To_Fire_PointsSlopeElevation_x_SlopeWilderness_AreaSoil_TypeCover_Type
00.9130.5320.0720.8700.9270.3690.1850.8750.0450.03828.00.05
10.9250.5160.0550.8660.9360.3660.1520.8680.0300.02528.00.05
20.9370.7260.4470.9210.9380.4730.1920.8530.1360.12311.00.02
30.9370.7240.4340.9370.9210.4630.1730.8660.2730.24529.00.02
40.9210.5070.0550.8660.9320.3680.1100.8600.0300.02528.00.05
50.9330.4830.0090.9060.9380.3600.2150.8410.0910.07628.00.02
60.8860.5410.0890.8740.8970.3740.1930.8720.1060.08928.00.05
70.9060.5310.0810.8740.9180.3730.1680.8680.0610.05128.00.05
80.8700.5400.0940.8780.8830.3790.1720.8700.1360.11528.00.05
90.8620.5370.0890.8980.8720.3770.1770.8690.1520.12728.00.05
Hillshade_NoonHydro_Road_Fire_DistanceHorizontal_Distance_To_RoadwaysHillshade_9amAvg_HillshadeElevationHorizontal_Distance_To_HydrologyHorizontal_Distance_To_Fire_PointsSlopeElevation_x_SlopeWilderness_AreaSoil_TypeCover_Type
5053440.8430.2500.2240.8980.8500.6660.1360.2210.1820.18730.02.01
5053450.8070.2500.2240.9090.8110.6620.1160.2240.2420.24930.02.01
5053460.7990.2490.2240.8940.8040.6580.0960.2280.2580.26330.02.01
5053470.8070.2490.2240.8740.8170.6550.0770.2310.2270.23230.02.01
5053480.8230.2490.2230.8820.8320.6530.0610.2340.2120.21630.02.01
5053490.8310.2490.2230.9060.8370.6500.0430.2380.1970.20030.02.01
5053500.8430.2490.2230.9170.8480.6460.0210.2410.1970.20030.02.01
5053510.8390.2490.2240.8980.8460.6430.0000.2450.1970.20023.02.01
5053520.8030.2510.2240.8700.8130.6410.0000.2480.2420.24523.02.01
5053530.7870.2550.2240.8310.7990.6380.0210.2520.2580.26023.02.01